docstr: Save the onnx model file to the disk.
  
  :param dirname: The dir location you want to save the onnx file.
docstr_tok: ["Save","the","onnx","model","file","to","the","disk",".",":","param","dirname",":","The","dir","location","you","want","to","save","the","onnx","file","."]
code: def export_onnx_file(self, dirname):
      """
      Save the onnx model file to the disk.
  
      :param dirname: The dir location you want to save the onnx file.
      """
      from bigdl.nano.utils.common import invalidInputError
  
      if self.backend.startswith("keras"):
          invalidInputError(
              False, "Currenctly, keras not support onnx method."
          )
  
      if self.distributed:
          invalidInputError(
              False,
              "export_onnx_file has not been supported for distributed "
              "forecaster. You can call .to_local() to transform the "
              "forecaster to a non-distributed version.",
          )
      import torch
  
      dummy_input = torch.rand(
          1,
          self.best_config["past_seq_len"],
          self.best_config["input_feature_num"],
      )
      self.best_model._build_onnx(dummy_input, dirname)
  
file_path: BigDL/python/chronos/src/bigdl/chronos/autots/model/base_automodel.py
imports: import os
  import json
  from bigdl.chronos.autots.utils import recalculate_n_sampling
  import warnings
label_desc: Use image node_id 10 for calling the BaseAutomodel obj's underlying member method code with example usage: obj.export_onnx_file(dirname) without return types